• The Journal of the Korea institute of electronic communication sciences
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• v.19 no.1
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• pp.233-240
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• 2024

In this study, we introduce a system for real-time monitoring of field conditions within an industrial complex using a 5G network UAV (: Unmanned Aerial Vehicle). When a monitoring event occurs in a sensor mounted on a UAV (detection of fire, harmful gas, or industrial disaster type human accident), key information from the sensor is transmitted to the UAS (: Unmanned Aerial System) application server. As a result of this information transmission and processing, managers or operators of the Industrial Complex Corporation were able to secure legal basis data for fatal accidents, fires, and detection of harmful gases at sites within the Industrial Complex Corporation through trigger processing for each accident risk situation.

• Nuclear Engineering and Technology
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• v.55 no.12
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• pp.4695-4702
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• 2023

Nuclear power plants play a pivotal role in the global energy infrastructure, fulfilling a substantial share of the world's energy requirements in a sustainable way. The management of these facilities, especially the handling of spent nuclear fuel (SNF), necessitates meticulous inspections to guarantee operational safety and efficiency. However, the prevailing inspection methodologies lean heavily on human operators, which presents challenges due to the potential hazards of the SNF environment. This study introduces the design of a novel Pre-Batched Inspection Strategy (PBIS) that integrates robotic automation and image processing techniques to bolster the inspection process. This methodology deploys robotics to undertake tasks that could be perilous or time-intensive for humans, while image processing techniques are used for precise identification of SNF targets and regulating the robotic system. The implementation of PBIS holds considerable promise in minimizing inspection time and enhancing worker safety. This paper elaborates on the structure, capabilities, and application of PBIS, underlining its potential implications for the future of nuclear energy inspections.

• Journal of KIISE:Databases
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• v.27 no.2
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• pp.165-174
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• 2000

Recent researches about range queries in OLAP are only concerned with applying an aggregation operator over a certain region. However, data analysts in real world need not only the simple range query pattern but also an extended range query pattern that finds ranges which satisfy a special condition specified by using several aggregation operators. In this work, we define the general form of the extended range query and propose an efficient processing method for the 'MAX -of-SUM' query, which is the representative form of the extended range query pattern. The MAX-of-SUM query finds the range which has the maximum range sum value in data cube where the size of the range is given. The proposed query processing method is based on the prediction of the scope of the range sum values. That is, the search space on the query processing can be reduced by using the result of the prediction, and hence, the query response time is also reduced.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.2
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• pp.305-312
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• 2020

The Privacy Act stipulates that the privacy policy document, which is a privacy statement, should be disclosed in order to guarantee the rights of the information subjects, and the Fair Trade Commission considers the privacy policy as a condition and conducts an unfair review of the terms and conditions under the Terms and Conditions Control Act. However, the information subjects tend not to read personal information because it is complicated and difficult to understand. Simple and legible information processing policies will increase the probability of participating in online transactions, contributing to the increase in corporate sales and resolving the problem of information asymmetry between operators and information entities. In this study, complex personal information processing policies are analyzed using deep learning, and models are presented for acquiring simplified personal information processing policies that are highly readable by the information subjects. To present the model, the personal information processing policies of 258 domestic companies were established as data sets and analyzed using deep learning technology.

• Journal of Korean Society for Geospatial Information Science
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• v.20 no.2
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• pp.81-91
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• 2012

As the recent development of the ubiquitous computing environment, u-GIS is being highlighted as the core technology of the ubiquitous computing environment, and thereby, studies on spatio-temporal data are being actively conducted. In this u-GIS environment, it is still difficult for existing mobile devices to efficiently manage the massive spatio-temporal data of u-GIS that are increasing day by day. Therefore, this paper develops a spatio-temporal query processing system for mobile devices in order to solve the problem. The system provides various spatio-temporal operators to insert/delete/update/search spatio-temporal data and supports a query optimization function that uses a spatio-temporal index for the flash memory and a spatio-temporal histogram for guaranteeing query execution speed. Lastly, by applying the spatio-temporal query processing system developed in this paper to the virtual scenario, this paper has proved that the system can be utilized in various application fields necessary to process spatio-temporal data in the mobile environment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.10
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• pp.1861-1871
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• 1994

This paper presents efficient real time software implementation methods for the grayscale morphological composite function processing (FP) system. The proposed method is based on a matrix representation of the composite FP system using a basis matrix composed of structuring elements. We propose a procedure to derive the basis matrix for composite FP systems with any grayscale structuring element (GSE). It is shown that composite FP operations including morphological opening and closing are more efficiently accomplished by a local matrix operation with the basis matrix rather than cascade operations, eliminating delays and requiring less memory storage. In the second part of this paper, a VLSI implementation architecture for grayscale morphological operators is presented. The proposed implementation architecture employs a bit-serial approach which allows grayscale morphological operations to be decomposed into bit-level binary operation unit for the p-bit grayscale singnal. It is shown that this realization is simple and modular structure and thus is suitable for VLSI implementation.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.15 no.4
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• pp.268-276
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• 2015

A ship's sailing route or plan is determined by the master as the decision maker of the vessel, and depends on the characteristics of the navigational environment and the conditions of the ship. The trajectory, which appears as a result of the ship's navigation, is monitored and stored by a Vessel Traffic Service center, and is used for an analysis of the ship's navigational pattern and risk assessment within a particular area. However, such an analysis is performed in the same manner, despite the different navigational environments between coastal areas and the harbor limits. The navigational environment within the harbor limits changes rapidly owing to construction of the port facilities, dredging operations, and so on. In this study, a support vector machine was used for processing and modeling the trajectory data. A K-fold cross-validation and a grid search were used for selecting the optimal parameters. A complicated traffic route similar to the circumstances of the harbor limits was constructed for a validation of the model. A group of vessels was composed, each vessel of which was given various speed and course changes along a specified route. As a result of the machine learning, the optimal route and voyage data model were obtained. Finally, the model was presented to Vessel Traffic Service operators to detect any anomalous vessel behaviors. Using the proposed data modeling method, we intend to support the decision-making of Vessel Traffic Service operators in terms of navigational patterns and their characteristics.

• The KIPS Transactions:PartB
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• v.16B no.4
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• pp.327-331
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• 2009

In fuzzy logic, aggregating uncertainties is generally achieved by means of operators such as t-norms and t-conorms. However, existing aggregation operators have some disadvantages as follows : First, they are situation-independent. Thus, they may not be properly applied to dynamic aggregation process. Second, they do not give an intuitional sense to decision making process. To solve these problems, we propose a new $\varepsilon$-AMDA (Aggregation based on the fuzzy Multidimensional Decision Analysis) algorithm to reflect degrees of strength for option i (i = 1, 2, ..., n) in the decision making process. The $\varepsilon$-AMDA algorithm makes adaptive aggregation results between min (the most weakness for an option) and max (the most strength for an option) according to the values of the parameter representing degrees of strength for an option. In this respect, it may be applied to dynamic aggregation process. In addition, it provides a mechanism of the fuzzy multidimensional decision analysis for decision making, and gives an intuitional sense to decision making process. Thus, the proposed method aids the decision maker to get a suitable decision according to the degrees of strength for options (or alternatives).

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2015.07a
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• pp.310-311
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• 2015

Ships' tracking data are being monitored and collected by vessel traffic service center in real time. In this paper, we intend to contribute to vessel traffic service operators' decision making through extracting ships' tracking patterns and models based on these data. Support Vector Machine algorithm was used for vessel track modeling to handle and process the data sets and k-fold cross validation was used to select the proper parameters. Proposed data processing methods could support vessel traffic service operators' decision making on case of anomaly detection, calculation ships' dead reckoning positions and etc.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.2
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• pp.279-286
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• 2020

On February 4, 2020, the Personal Information Protection Act ("Privacy Act") was amended to facilitate the convergence and utilization of data, a key resource of the Fourth Industrial Revolution, and to support the development of the data industry. As the scope of the law applies to telecommunications operators, financial operators, and personal information processing providers, the scope of related dispute settlement is expected to increase. Therefore, this paper first introduces the role and function of the Personal Information Dispute Committee and the institutional standards for personal information dispute mediation, and researches the roles and issues that the Personal Information Dispute Mediation Committee should play in accordance with the revision of the Data 3 Law. In this study, For efficient operation of personal information dispute mediation, expert deliberation by field, new adjustment criteria for new industrial technologies, way to secure business continuity between the Personal Information Dispute Committee and the Personal Information Committee, Secure the link between the mediation decision and courts, and Suggested the strengthening of the operational standards for collective dispute mediation.